Method for measuring the frequency of continuous wave and wide pulse RF signals

ABSTRACT

A method for measuring the frequency of continuous wave and wide pulse RF signals using multi-purpose, commercial-off-the-shelf test devices, such as an RF signal down converter, a digitizer and a signal processor. The method is based on digitizing the RF signals and dividing the digitized data into blocks of discrete data points. An initial estimated frequency is calculated for the first block of data and used to generate a synthetic signal. The synthetic signal and individual block of data under analysis are summed and tested by a discrimination function through an iteration process to arrive at an estimated frequency for each block of data points. The results are averaged to arrive at the final calculated frequency for the RF signal. The method is suitable for real-time calculations of the RF signal frequency.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention relates to RF signals, and more particularly to aninexpensive method of measuring the frequency of Continuous Wave andWide Pulse RF signals in real-time or near real-time.

2. Description of Related Art

Radar and electronic counter measure (ECM) systems commonly employcontinuous wave (CW) or wide pulse (pulses with widths >5 microsec) RFsignals. The frequency of such an RF signal emitted by these systems isan important characteristic that must be accurately measured to assess asystem's performance.

The conventional method for measuring RF frequency is to use expensiveequipment such as electronic counters, spectrum analyzers, synchronousdetectors and digital frequency discriminators. Microwave counters EIP1230A and 1231A manufactured by EIP Microwave, Inc. and the HewlettPackard electronic counter HP 5361B are examples of instrumentscurrently in use to measure RF frequencies. These instruments, however,are expensive, bulky and require specialized hardware. They also do notprovide the required frequency measurement accuracy for state-of-the-artradar and ECM systems. The accuracy required for these systems is often<100 hertz for signals with frequencies of up to 40 gigahertz.

SUMMARY OF THE INVENTION

The developed technique uses standard test devices such as an RF signaldown converter, a digitizer, and a signal processor to achieve the sameor better measurement accuracy as more expensive frequency measurementdevices. Because these standard test devices are multi-purpose,commercial off-the-shelf equipment, the cost of implementing theinvention is low.

The method for measuring the frequency of continuous wave or wide pulseRF signals comprises down convening the RF signal to a signal having anintermediate frequency and then digitizing the intermediate frequencysignal. The digitized signal is divided into blocks of discrete datapoints. The first block of data points is processed to calculate aninitial estimated frequency representative of the RF signal. The initialestimated frequency is used as the starting point to calculate thefrequency of the individual remaining blocks of discrete data pointsthrough an iteration process. Generally, the iteration process includesgenerating a synthetic signal as a function of the initial estimatedfrequency and the block of discrete data points under analysis andsumming the synthetic signal and data to produce a sum signal. Adiscrimination function tests the sum signal for a particularcharacteristic, such as monotonicity or minimum value. A positive and/ornegative incremental frequency value is added to the initial estimatedfrequency to create a new estimated frequency, and the incrementalfrequency value is reduced in magnitude and tested against a thresholdvalue. If the incremental value is greater than the threshold value thena new synthetic signal is generated as a function of the new estimatedfrequency and the data points under analysis. The new synthetic signaland data points are summed and tested using the same discriminationfunction. The iteration process continues until the incremental value isbelow the threshold, and the frequency calculated in that particularloop is the calculated final frequency for that data block underanalysis. The same procedure continues for the remaining blocks of datapoints. The final calculated frequency for the RF signal is the averageof the frequencies calculated for all of the data blocks.

The objective of this invention is to provide an innovative CW/WidePulse RF frequency measurement technique using low cost commercialoff-the-shelf test equipment. The invention measures the frequency of RFsignals with a high degree of accuracy using only the RF signal outputof the unit under test (UUT) as the input to the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objects and advantages of this invention will beapparent on consideration of the following detailed description, takenin conjunction with the accompanying drawings, in which like referencecharacters refer to like parts throughout, and in which:

FIG. 1 is a block diagram of the RF signal acquisition procedure;

FIG. 2 is a flow diagram of a first embodiment for calculating thefrequency of continuous wave or wide pulse RF signals;

FIG. 3 is a flow diagram of a coarse and fine tuning loop;

FIG. 4 is a flow diagram of an alternate embodiment for calculating thefrequency of continuous wave or wide pulse RF signals;

FIG. 5 is a graphical illustration of the result of summing two signals;

FIG. 6 is a flow diagram for performing an iteration search to locatephase minimum; and

FIG. 7 is a flow diagram for performing an iteration search to determinethe frequency for a block of data points.

DETAILED DESCRIPTION OF THE INVENTION

The following detailed description, which describes only the preferredembodiment of the invention, is understood only to be an illustration ofthe best mode contemplated of carrying out the invention. As will berealized, the invention is capable of other and different embodiments,and its several details are capable of modifications in various obviousrespects, all without departing from the invention. Accordingly, thedrawings and description are to be regarded as illustrative in nature,and not as restrictive.

FIG. 1 illustrates the signal acquisition mechanism of the invention.The RF signal (CW or wide pulse) generated by the UUT is frequency downconverted to an intermediate frequency (IF). Mixer 22 receives both thetest signal from source 20 and a control frequency generated by a localoscillator 24. Mixer 22 outputs an IF signal as the difference betweenthe frequencies (i.e. Frequency_(RF) -Frequency_(control) =IF). The IFsignal passes through bandpass filter 26 to remove unwanted highfrequency components. The IF signal is sampled by a digitizer 28 andtransferred to a signal processor 30 to perform frequency analysis. Thepreferred IF is approximately from between 10 percent to about 25percent of the sampling frequency of digitizer 28.

In one embodiment, the acquired data from digitizer 28 is divided intoblocks of data points, preferably 512 data points per block. The blocksof date serve as the input to the frequency measurement algorithm, shownin FIG. 2. The first two data blocks are used to derive an initialestimate of the input RF signal frequency, f_(e) initial. This isaccomplished by performing a Fast Fourier Transform (FFT) on each of thefirst two data blocks 32, and a power spectrum analysis 34 of the resultyields the starting frequency estimate for the coarse tuning loop 36,described below. The tuning loop first calculates a coarse frequency foreach of the first two data blocks. The average of the two coarsefrequencies 38 is used as the initial frequency estimate f_(e) for thefine tuning loop which more finely calculates the frequency of theremaining data blocks 40. The final frequency measurement is the averageof the results of the fine tuning loops for many data blocks, afterrejection of outliers (where outliers are >2 standard deviations) 42 and44.

The coarse and fine tuning loops are both graphically illustrated inFIG. 3 and differ only in the source of the starting frequency and therange over which the binary search is performed. The coarse tuning loopuses as its starting frequency the frequency calculated at 36. The finetuning loop uses f_(e), determined in step 38.

In operation, the tuning loops each receive individual blocks of dataand omit all data points preceding the first maximum data point therebyrepresenting the block of data as a cosine function represented by:

    cos((2π*(f.sub.e +δ)*I)/f.sub.s)                  (1)

where f_(s) is the sampling frequency, f_(e) is the estimated frequency,δ is the frequency error estimate and I is the block data input. Thesignal is further down converted to a very low frequency (near DC)comprising an in-phase component 46 and a quadrature component 47. Thein-phase component 46 consists of multiplying the cosine functiondefined by equation (1) by a synthetic signal characterized by:

    sin(2π*f.sub.e *I)/f.sub.s)                             (2)

resulting in:

    -1/2[sin((2π(2f.sub.e +δ)/f.sub.s)*I)-sin(2π(δ/f.sub.s)*I)]      (3)

The quadrature determination 47 is characterized by first performing aHilbert transform on the input data block using any of commonly knownmethods, such as FFT or Filter-based methods. The resultant signal ismultiplied by a synthetic signal characterized by:

    cos((2π*f.sub.e *I)/f.sub.s)                            (4)

resulting in:

    1/2[sin((2π(2f.sub.e +δ)/f.sub.s)*I)+sin(2π(δ/f.sub.s)*I)](5)

The result of summing equations (3) and (5) is a signal with twocomponents--the "sum" component containing the sum of the estimatedf_(e) and the error of the estimate relative to the actual frequency,and the "difference" component containing the error alone. In theory,the summation function results in:

    sin(2π(δ/f.sub.s)I)                               (6)

where the sum component is zero. Filtering 48 is preferred to remove anyresidual sum components. A smoothing and integration function 49 furtherenhances the signal-to-noise ratio of the filter output. For smallvalues of δ, the "difference" frequency component can be approximated bya monotonically increasing or decreasing discrimination function(sin(x)=x) 50. A binary search technique 52 is used to refine the downconversion frequency until monotonicity of the discrimination functionis embedded in the noise generated by the down conversion process. Ifδ>0, then the discriminate function is monotonically increasing andf_(e) is too low and must be increased by some incremental frequencyvalue; if δ<0, then the result is monotonically decreasing and f_(e) istoo high and must be decreased by some incremental frequency value. Thesignal is continually cycled through the tuning loop until the incrementis below some threshold. At that determination, the calculated frequencyis the last incremented f_(e).

FIGS. 4 and 5 illustrate an alternate embodiment of the invention. Thisembodiment takes advantage of the fact that when two RF signals,identical in frequency and magnitude, but differing in phase by 180°,are added together, the result is a 0 signal level.

The acquired data from digitizer 28 is divided into blocks of datapoints, preferably, between 256 to 1024 data points per block. The firstdata block is used to derive an initial estimate of the input signalfrequency. An FFT is performed on this block 60, and power spectrumanalysis 62 of the result yields the frequency used as the startingpoint, f_(initial), for the iterative phase search 64. The 180°out-of-phase point of the first data block input signal, can be found bysynthesizing a signal having an amplitude approximating that of theactual signal and having a frequency f_(initial) and determining thephase at which the sum of the synthesized signal and the actual inputsignal is minimized, Φ_(min), as illustrated in FIG. 5. Enough pointsmust be used so that the accuracy of the starting point frequency usedin the phase portion of the iterative search does not cause a largeerror in the phase estimate. A 1024 point FFT yields sufficient accuracyso that the frequency derived from the first data block can be used asthe starting point for the remainder of the data blocks. Preferably, iffewer than 1024 points are available in each data block, then for theinitial FFT, the remainder of the 1024 points can be zero-filled.

FIG. 6 illustrates a preferred iterative phase search method. Holdingf_(initial) constant, the phase, Φ, of the synthesized signal is firstvaried through a search interval δ.sub.Φ having a range from 0° to 360°in steps of N degrees 76. The phase, Φ_(min), is calculated where theminimum sum of the synthesized signal and the input data occurs. In eachsubsequent step, the search range interval is reduced to [Φ_(min) -stepsize of previous step] and [Φ_(min) +step size of previous step] 80.Step size N is reduced by some factor, M (typically 4 to 10) 82. Thisiteration continues until the step size is below some arbitrary accuracythreshold 84 and a final Φ_(min) is determined for the first data block86.

Referring again to FIG. 4, the phase value, Φ_(min), is used in thefrequency iterative search 66 to calculate the estimated frequency forthe first data block as illustrated in FIG. 7. The frequency of thefirst data block input signal can be found by synthesizing a signalhaving an amplitude approximating that of the actual signal and havingthe phase Φ_(min) and determining the frequency at which the sum of thesynthesized signal and the actual input signal is minimized, asillustrated in FIG. 5. Assuming the estimated frequency is in the FFTbin from step 60, the frequency is varied through a search intervalδ_(f) to cover approximately 1 to 2 FFT bins in steps of N Hz. Thefrequency at which the minimum sum of the synthesized signal and theinput data occurs, f_(min), is then used as the starting point for thenext step of the search. In each subsequent step, the interval isreduced to [f_(min) -step size of previous step] and [f_(min) +step sizeof previous step] 92. Step size N is reduced by some factor, M(typically from 4 to 10) 94. This iteration continues until the stepsize is below some arbitrary accuracy threshold and a final f_(min) isdetermined for the first data block.

The result of the iterative search performed on the first data block,f_(min), is used as the starting frequency for the iterative phasesearch 68 performed on the remaining data blocks. The Φ_(min) determinedfrom the iterative phase search is then input into the iterativefrequency search 70. A final f_(min) is calculated for each data block.Accuracy may be improved further by using the results of the previousphase/frequency search on a previous data block as the respective phaseand frequency inputs to the phase/frequency search on a subsequent datablock. The final frequency measurement is the average of the results forall but the first of the data blocks, after the rejection of outliers(where outliers are > than 2 standard deviations) 72 and 74.

It will be understood that the particular embodiments described aboveare only illustrative of the principles of the present invention, andthat various modifications could be made by those skilled in the artwithout departing from the scope and spirit of the present invention,which is limited only by the claims that follow.

What is claimed is:
 1. A method for measuring the frequency ofcontinuous wave or wide pulse RF signals comprising:(a) down conveningsaid RF signal to a signal having an intermediate frequency: (b)digitizing said intermediate frequency signal; (c) dividing saiddigitized data sample into blocks of discrete data points: (d)calculating an estimated frequency for a first data block; (e)calculating the frequency of the individual remaining blocks of discretedata points through an iteration process comprising:(i) generating asynthetic signal as a function of said estimated frequency and saidblock of discrete data points under analysis and summing said syntheticsignal and said data block under analysis to produce a sum signal; (ii)applying a discrimination function to test said sum signal; (iii) addingan incremental frequency value to said estimated frequency to create anew estimated frequency; (iv) testing said incremental frequency valueagainst a threshold value; (v) reducing the magnitude of saidincremental frequency value; and (vi) repeating steps (i) through (v)using said new estimated frequency if said incremental frequency valueis greater than said threshold value; wherein the calculated frequencyfor said individual data block under analysis is said new estimatedfrequency of (iii) when said incremental frequency value is less thansaid threshold value; and (f) calculating said frequency of said RFsignal by averaging said frequencies calculated in (e) for each datablock.
 2. The method of claim 1 wherein step (i) further comprises thesteps:(a) generating a first intermediate synthetic signal bymultiplying said data block by an in-phase determination characterizedby

    sin((2π*f.sub.e *I)/f.sub.s)

(c) generating a second intermediate synthetic signal by performing aHilbert transform on said data block and multiplying the result of saidtransform by a quadrature determination characterized by

    cos((2π*f.sub.e *I)/f.sub.s)

(d) summing said first and second intermediate synthetic signals,wherein said sum signal comprises a sum component and a differencecomponent; and (e) filtering out said sum component from said sumsignal.
 3. The method of claim 2 further comprising omitting all datapoints preceding the first maximum data point of said block of datapoints.
 4. The method of claim 2 wherein said discrimination functiontests whether said sum signal monotonically increases or decreases. 5.The method of claim 1 wherein said discrimination function tests for theminimum value of said sum signal.
 6. A method for measuring thefrequency of continuous wave or wide pulse RF signals comprising:(a)down converting said RF signal to a signal having an intermediatefrequency; (b) digitizing said intermediate frequency signal; (c)dividing said digitized data sample into blocks of discrete data points;(d) calculating an initial estimated frequency for said first datablock; (e) generating a first synthetic signal having an amplitudeapproximating that of a subsequent block of data points under analysisand having said initial estimated frequency; (f) determining the phaseangle, called phase minimum, at which the sum of said first synthesizedsignal and said data points is minimized (g) generating a secondsynthetic signal having an amplitude approximating that of said block ofdata points under analysis and having phase angle phase minimum; (h)determining the frequency, called frequency minimum, at which the sum ofsaid second synthesized signal and said data points is minimized; and(i) calculating said frequency of said RF signal by averaging saidfrequencies calculated in (h) for each data block.
 7. The method ofclaim 6 wherein the step of determining said phase minimum is aninteration process comprising the steps of:(a) varying the phase angleof said first synthetic signal through an interval having a start phaseand an end phase in steps of N degrees; (b) determining the phase angleat which the sum of said first synthesized signal and said data blockunder analysis is minimized; (c) reducing said interval and said N valueand repeating step (b), wherein said phase minimum is said phase angledetermined in (b) when said value N is less than a threshold value. 8.The method of claim 6 wherein the step of determining said frequencyminimum is an iteration process comprising the steps of:(a) varying thefrequency of said second synthetic signal through an interval having astart frequency and an end frequency in steps of N Hz; (b) determiningthe frequency at which the sum of said second synthesized signal andsaid data block under analysis is minimized; (c) reducing said intervaland said N value and repeating step (b), wherein said frequency minimumis said frequency determined in (b) when said value N is less than athreshold value.